Current landscape of clinical trials for HPV-positive head and neck squamous cell carcinoma (HNSCC)
Bibliographic record
Abstract
This study aims to determine the current state of clinical trials regarding HPV-positive head and neck squamous cell carcinoma (HNSCC). Clinical trials were filtered to fit the study's aim using Clinicaltrials.gov: trials concerning HNSCC specifically those related to HPV done between January 2005 and December 2020 were extracted and information regarding location, duration, phases, patient recruitment, trial status, results, primary outcome, type of intervention and publication status were collected and analysed. As a result, 123 trials were included. North American countries (USA and Canada) conducted more than two-thirds of the trials (72.4%) compared to European countries and the rest of the world. Trials in phase II constituted more than half of those included in this study (53.7%). From the 123 trials included in this study, only 30 had their NCT identification number linked to publications, but less than half (46.7%) of the publications stemmed from trials with results. Drug combination was the most widely studied treatment modality. Despite falling in the middle of the spectrum with respect to the number of trials when compared to other diseases, our research highlights the need for even more trials tackling multiple aspects of HPV-positive HNSCC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.235 | 0.378 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".